Abstract: Patch (1) for sealing an amniotic membrane, wherein the patch (1) comprises a support (11) and an adhesive (12) that is activated in presence of amniotic liquid or a wet environment. Device for placing said patch (1) comprising a cannula (2) for inserting said patch (1) in a rolled-up position, said cannula (2) being provided with a handle (3); and a dipstick (4) provided with a pusher (5), said dipstick (4) being inserted inside the cannula (2) in the use position. The patch adheres efficiently on the amniotic membrane, adapts to the elastic properties of this membrane, and by attaching only to the amnion it does not interfere with the natural sliding movements of one membrane against each other, together with the device to ensure that the patch is placed in the proper position without damaging the membrane.

Abstract: Techniques for assessing a tissue condition and diagnosing, assessing the prognosis of, or the risk for pathological conditions are disclosed. The technique may include an image acquiring module adapted to receive an image comprising at least a portion of animal or human tissue, a delineation module adapted to indicate an analysis zone in said acquired image, a feature extraction module adapted to extract quantitative information from said analysis zone and a machine learning module adapted to receive said extracted information and apply at least one detection algorithm to assess a condition of said tissue. The feature extractor module may have at least a rotation compensation module to compensate for the rotation of the analysis zone.

Abstract: Techniques for assessing a tissue condition and diagnosing, assessing the prognosis of, or the risk for pathological conditions are disclosed. The technique may include an image acquiring module adapted to receive an image comprising at least a portion of animal or human tissue, a delineation module adapted to indicate an analysis zone in said acquired image, a feature extraction module adapted to extract quantitative information from said analysis zone and a machine learning module adapted to receive said extracted information and apply at least one detection algorithm to assess a condition of said tissue. The feature extractor module may have at least a rotation compensation module to compensate for the rotation of the analysis zone.

Abstract: Equipment for infrared vision of anatomical structures applicable to assist the physicians in endoscopic, fetoscopic or laparoscopic operations and methods for signal processing to enhance said vision, comprising two units that work together: a multimodal or multispectral imaging unit, constituted by a device comprising an endoscope or fetoscope or laparoscope, and additional optical systems to acquire multimodal images of the interior of the patient's body; and an image processing unit, to which said images are transferred, comprising processing devices with a navigation interface which process said images and display the patient's enhanced anatomical map image and the endoscope location, equipped with hardware and software that apply at least five different vision-enhancing methods, namely normalization, segmentation, tracking, mapping and fusion.